All Outputs (2)

Improving the development and reusability of Industrial AI through Semantic Models (2024)
Conference Proceeding
Martínez-Arellano, G., & Ratchev, S. (in press). Improving the development and reusability of Industrial AI through Semantic Models.

Despite some of the success of AI, particularly machine learning, in industrial applications such as condition monitoring, quality inspection and asset control , solutions are typically bespoke and not robust in the long term. There is a considerable... Read More about Improving the development and reusability of Industrial AI through Semantic Models.

Multi-agent cooperative swarm learning for dynamic layout optimisation of reconfigurable robotic assembly cells based on digital twin (2024)
Journal Article
Wang, L., Wang, Z., Gumma, K., Turner, A., & Ratchev, S. (in press). Multi-agent cooperative swarm learning for dynamic layout optimisation of reconfigurable robotic assembly cells based on digital twin. Journal of Intelligent Manufacturing, https://doi.org/10.1007/s10845-023-02229-7

To meet the requirement of product variety and short production cycle, reconfigurable manufacturing system is considered as an effective solution in addressing current challenges, such as increasing customisation, high flexibility and dynamic market... Read More about Multi-agent cooperative swarm learning for dynamic layout optimisation of reconfigurable robotic assembly cells based on digital twin.